The present invention relates to a method for providing occupant classification in a motor vehicle.
K. Billen, L. Federspiel, P. Schockmehl, B. Serban, and W. Scherrel""s xe2x80x9cOccupant Classification System for Smart Restrained Systems,xe2x80x9d SAE Paper, 1999, pages 33-38, describes a seat mat having a sensor matrix, which is used for generating a seat profile of different persons and objects. Moreover, this seat profile is continuously checked. From this seat profile, features are determined that are used for occupant classification.
The method for occupant classification in a vehicle according to the present invention has the advantage that for every feature that was determined from the seat profile, a weight estimate is carried out for each of the features, the individual weight estimates then being used for determining the weight of the occupant and, thus, for occupant classification. Thus, it is ensured that a single feature cannot distort the occupant classification. In this context, all features are weighted equally. Furthermore, the method can, therefore, be easily expanded to a plurality of features without increasing the complexity of the method according to the present invention.
Moreover, it is advantageous that a measure of quality is used via which bad (inaccurate) seat profiles are discarded, so that there are no incorrect classifications due to bad seat profiles. In particular, this is to be viewed as a function of time, since a seat profile can exhibit poor quality for different reasons at different instants, so that it is to be assumed that the occupant classification resulting from the seat profile is faulty. The method according to the present invention, therefore, results in a reliable occupant classification and, thus, for connected systems, such as a restraint system, improved operability of these systems.
It is particularly advantageous that the weight estimate for the feature in question is calculated via a stored function that was previously experimentally determined. Thus, this function relates the feature value to a weight value. Consequently, a weight estimate for a particular feature value is possible in a simple manner.
Furthermore, it is advantageous that the occupant classification is used for a restraint system. As such, it is possible, particularly for a multi-stage airbag as the restraint system, to be activated in such a manner that none of the passengers to be protected are injured. The restraining force that the airbag exerts on the person or the object is exerted as a function of the specific occupant class. In this context, every stage of the airbag corresponds to a certain force value. The airbag exerts a greater restraining force on a heavy person than on a lighter one.
Moreover, it is advantageous that the ischial tuberosity distance and/or the seat profile size is/are used as the features. They are simple features that can be easily determined from the established seat profile. However, further features are also possible here.
Finally, it is also advantageous that a device for implementing the method according to the present invention is present, the device having a seat mat including the sensor matrix and a processor for determining features and classifying occupants. In this context, the processor is advantageously connected to the control unit for the restraint system.